Dependency assessment interface for components of graphical user interfaces

ABSTRACT

A system and method is disclosed for configuring a performance analytics (PA) system for processing key performance indicators of a managed network. The PA system may include a database containing PA entity records, each including data associated with a respective PA entity. Each PA entity may be a software and/or hardware component of the PA system. The system also includes a dependency assessment tree having respective nodes corresponding to the respective PA entities and branches connecting functionally dependent nodes of PA. The PA system may be configured to: transmit information to a client device for displaying a graphical representation of one or more respective PA entities; receive a request from the client device for dependency information for a first PA entity; and transmit to the client device a graphical representation of a first portion of the dependency assessment tree depicting the first PA entity and associated dependency nodes.

BACKGROUND

Managed networks may include various types of computer networks that canbe remotely administered. This management may involve one or morecomputing devices disposed with a remote network management platformcollecting information about the configuration and operational states ofsoftware applications executing on behalf on the managed network, andthen presenting representations of this information by way of one ormore user interfaces. The user interfaces may be, for instance,web-based user interfaces. In some instances, remote management ofnetworks may be provided by a third party, such as a service provider orvendor.

Some of the collected information may relate to key performanceindicators (KPIs). KPIs include any sort of measurement, reading, ordata that is relevant to the managed network. Thus, KPIs may reflectperformance of computing devices on the network itself (e.g., memoryutilization, processor utilization, transactions per second) orperformance of higher-level applications executing on the remote networkmanagement platform (e.g., a number of times per day that users on themanaged network have requested a particular type of technicalassistance). Among other capabilities, the user interfaces may be ableto display KPIs in numerous visualizations, such as charts, graphs, ortables.

Monitoring, analysis, and visualization of KPIs may be implemented as aspecific facility or environment within an overall remote networkmanagement system, and may involve databases and servers in orassociated with a managed network as well as end-user devices, such asclient devices with graphical user interfaces (GUIs). Visualization andanalysis tools may include various software components, which may beupdated and/or revised from time to time. Therefore, in addition tofunctional capabilities used in practice, stability and integrity ofvisualization and analysis tools during and after updates and/orrevisions may also be of interest.

SUMMARY

A performance monitoring and analysis system may implement monitoring,analysis, and visualization of KPIs within an overall remote networkmanagement system as a Performance Analytics (PA) application programwith extendable features and capabilities. In accordance with exampleembodiments, a PA application program may include program componentsconfigured to operate on one or more servers and databases in a remotenetwork management system, as well as client-based program components,such as web applications with graphical features and functions,configured to operate on client devices having graphical user interfaces(GUIs). Server and database programs may collect, record, and managedata related to and/or indicative of performance from a managed network,while client applications may provide end users with tools to defineKPIs and configure and control monitoring of KPIs, as well as toretrieve KPI data from databases or servers for visualization, analysis,and evaluation of KPIs. A PA system may therefore include a PAapplication program, as well as supporting hardware components andsystems, such as servers, databases, computing devices, and clientdevices.

More particularly, data related to and/or indicative of performance mayinclude data directly related to performance, such as incident orproblem reports logged by end users or IT personnel, for example. Otherforms of direct performance data may include monitored or measuredresource utilization (e.g., memory, CPU, and network bandwidth).Performance data may also include data related to the mission of anorganization, such as sales or financial results. In addition,performance data may include indirect or derived forms of performancemetrics that may involve relationships between two or more forms ofrecorded or monitored data. All or some of the various types and formsof performance data may be stored in one or more network databases, andbe available within the PA context for analysis, viewing, and evaluationvia direct transactions with the databases, or via intermediary serverapplications, for example.

Defining or creating KPIs may entail identifying directly available orderivable variables that may be indicative of behavior or performancewhen monitored in time. Configuration and control may entail settingparameters that determine monitoring frequency and duration, as well asvarious filters applied during collection and/or derivation of KPI data.KPIs may thus be considered descriptions of data that form the basis ofthe indicators, as well as parameters and filters. The actualperformance analysis or assessment for a given KPI then utilizes actualdata specified and collected according to the given KPI.

In a large managed network, the breadth and depth of data that may beutilized by a PA system can be quite large. Correspondingly, the numberand variety types of possible interrelationships between monitored orlogged data that may form the basis of KPIs can also be large. Inaddition, the interrelationships and dependencies of functionalcomponents of a PA system can be large and complex. These factorspresent challenges to designing and implementing a PA system thatprovides versatility and flexibility to end users without imposing theunderlying complexities on end users when they invoke operations thatrely on or need to account for those complexities. It would therefore bedesirable to devise and implement user interfaces that providestreamlined and efficient graphical tools for carrying out PA tasksinvolving complex relationships among and between performance data, andbetween program components of the PA system.

Accordingly, a first example embodiment may involve a performanceanalytics (PA) system disposed within a computational instance of aremote network management platform that is associated with a managednetwork and configured for processing and analysis of performance dataof the managed network, the PA system comprising: a database containinga plurality of PA entity records, each PA entity record comprising datafor configuring a graphical representation of a respective PA entity ona graphical user interface (GUI) within the managed network, wherein therespective PA entity is a component of the PA system configured forprocessing one or more key performance indicators (KPIs) of the managednetwork, and is implemented as at least one of a software component or ahardware system, and wherein each PA entity record further comprisesinformation specifying a logical location of the respective PA entity ina dependency assessment tree, the dependency assessment tree comprising(i) respective nodes corresponding to the respective PA entities of theplurality of PA entity records and (ii) branches connecting nodes of PAentities between which there is a functional dependence; and a computingdevice operational to execute a dependency assessment software program,wherein the dependency assessment software program is configured to:transmit, to a client device, information for displaying in a GUI of theclient device the graphical representation of one or more of therespective PA entities, receive, from the client device, a first requestfor dependency information for a first PA entity from among the one ormore respective PA entities, and responsive to the first request,transmit, to the client device, a graphical representation of a firstportion of the dependency assessment tree depicting the first PA entityand both one or more dependency nodes corresponding to PA entitieshaving a functional dependency relationship with the first PA entity,and connecting branches.

In a second example embodiment may involve a client device operable toconfigure a performance analytics (PA) system disposed within acomputational instance of a remote network management platform that isassociated with a managed network, the PA system being configured forprocessing and analysis of performance data of the managed network, theclient device configured to: display, in a graphical user interface(GUI), a graphical representation of one or more PA entities, wherein adatabase of the remote network management platform contains a pluralityof PA entity records, each PA entity record comprising data forconfiguring the graphical representation of a respective PA entity,wherein the respective PA entity is a component of the PA systemconfigured for processing one or more key performance indicators (KPIs)of the managed network, and is implemented as at least one of a softwarecomponent or a hardware system, and wherein each PA entity recordfurther comprises information specifying a logical location of therespective PA entity in a dependency assessment tree, the dependencyassessment tree comprising (i) respective nodes corresponding to therespective PA entities of the plurality of PA entity records and (ii)branches connecting nodes of PA entities between which there is afunctional dependence; receive, via the GUI, input that selects a firstPA entity from among the displayed one or more respective PA entities;responsive to transmitting, to a computing device disposed within thecomputational instance of the remote network management platform, afirst request for dependency information for the selected first PAentity, receive a graphical representation of a first portion of thedependency assessment tree depicting the first PA entity and both one ormore dependency nodes corresponding to PA entities having a functionaldependency relationship with the first PA entity, and connectingbranches; and display, in the GUI, the graphical representation of thefirst portion of the dependency assessment tree.

In a third example embodiment may involve a method for configuring aperformance analytics (PA) system disposed within a computationalinstance of a remote network management platform that is associated witha managed network, the PA system being configured for processing andanalysis of performance data of the managed network, the method operableon a computing device disposed within the remote network managementplatform, the method comprising: transmitting, to a client device,information for displaying in a graphical user interface (GUI) of theclient device a graphical representation of one or more respective PAentities, wherein a database of the remote network management platformcontains a plurality of PA entity records, each PA entity recordcomprising data for configuring the graphical representation of arespective PA entity, wherein the respective PA entity is a component ofthe PA system configured for processing one or more key performanceindicators (KPIs) of the managed network, and is implemented as at leastone of a software component or a hardware system, and wherein each PAentity record further comprises information specifying a logicallocation of the respective PA entity in a dependency assessment tree,the dependency assessment tree comprising (i) respective nodescorresponding to the respective PA entities of the plurality of PAentity records and (ii) branches connecting nodes of PA entities betweenwhich there is a functional dependence; receiving, from the clientdevice, a first request for dependency information for a first PA entityfrom among the one or more respective PA entities; and responsive to thefirst request, transmitting, to the client device, a graphicalrepresentation of a first portion of the dependency assessment treedepicting the first PA entity and both one or more dependency nodescorresponding to PA entities having a functional dependency relationshipwith the first PA entity, and connecting branches.

In a fourth example embodiment, a system may include various means forcarrying out each of the operations of the third example embodiment.

These as well as other embodiments, aspects, advantages, andalternatives will become apparent to those of ordinary skill in the artby reading the following detailed description, with reference whereappropriate to the accompanying drawings. Further, this summary andother descriptions and figures provided herein are intended toillustrate embodiments by way of example only and, as such, thatnumerous variations are possible. For instance, structural elements andprocess steps can be rearranged, combined, distributed, eliminated, orotherwise changed, while remaining within the scope of the embodimentsas claimed.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a schematic drawing of a computing device, inaccordance with example embodiments.

FIG. 2 illustrates a schematic drawing of a server device cluster, inaccordance with example embodiments.

FIG. 3 depicts a remote network management architecture, in accordancewith example embodiments.

FIG. 4 depicts a communication environment involving a remote networkmanagement architecture, in accordance with example embodiments.

FIG. 5A depicts another communication environment involving a remotenetwork management architecture, in accordance with example embodiments.

FIG. 5B is a flow chart, in accordance with example embodiments.

FIG. 6A depicts a performance analytics dashboard in the form of agraphical user interface, in accordance with example embodiments.

FIG. 6B depicts a performance analytics dashboard in the form of agraphical user interface, in accordance with example embodiments.

FIG. 7 depicts an example view of an example dependency assessment tree,in accordance with example embodiments.

FIG. 8 depicts an example top-down view of an example dependencyassessment tree, in accordance with example embodiments.

FIG. 9 depicts an example bottom-up view of an example dependencyassessment tree, in accordance with example embodiments.

FIG. 10A depicts another example top-down view of an example dependencyassessment tree, in accordance with example embodiments.

FIG. 10B depicts another example bottom-up view of an example dependencyassessment tree, in accordance with example embodiments.

FIG. 11 is a flow chart, in accordance with example embodiments.

DETAILED DESCRIPTION

Example methods, devices, and systems are described herein. It should beunderstood that the words “example” and “exemplary” are used herein tomean “serving as an example, instance, or illustration.” Any embodimentor feature described herein as being an “example” or “exemplary” is notnecessarily to be construed as preferred or advantageous over otherembodiments or features unless stated as such. Thus, other embodimentscan be utilized and other changes can be made without departing from thescope of the subject matter presented herein.

Accordingly, the example embodiments described herein are not meant tobe limiting. It will be readily understood that the aspects of thepresent disclosure, as generally described herein, and illustrated inthe figures, can be arranged, substituted, combined, separated, anddesigned in a wide variety of different configurations. For example, theseparation of features into “client” and “server” components may occurin a number of ways.

Further, unless context suggests otherwise, the features illustrated ineach of the figures may be used in combination with one another. Thus,the figures should be generally viewed as component aspects of one ormore overall embodiments, with the understanding that not allillustrated features are necessary for each embodiment.

Additionally, any enumeration of elements, blocks, or steps in thisspecification or the claims is for purposes of clarity. Thus, suchenumeration should not be interpreted to require or imply that theseelements, blocks, or steps adhere to a particular arrangement or arecarried out in a particular order.

I. INTRODUCTION

A large enterprise is a complex entity with many interrelatedoperations. Some of these are found across the enterprise, such as humanresources (HR), supply chain, information technology (IT), and finance.However, each enterprise also has its own unique operations that provideessential capabilities and/or create competitive advantages.

To support widely-implemented operations, enterprises typically useoff-the-shelf software applications, such as customer relationshipmanagement (CRM) and human capital management (HCM) packages. However,they may also need custom software applications to meet their own uniquerequirements. A large enterprise often has dozens or hundreds of thesecustom software applications. Nonetheless, the advantages provided bythe embodiments herein are not limited to large enterprises and may beapplicable to an enterprise, or any other type of organization, of anysize.

Many such software applications are developed by individual departmentswithin the enterprise. These range from simple spreadsheets tocustom-built software tools and databases. But the proliferation ofsiloed custom software applications has numerous disadvantages. Itnegatively impacts an enterprise's ability to run and grow itsoperations, innovate, and meet regulatory requirements. The enterprisemay find it difficult to integrate, streamline and enhance itsoperations due to lack of a single system that unifies its subsystemsand data.

To efficiently create custom applications, enterprises would benefitfrom a remotely-hosted application platform that eliminates unnecessarydevelopment complexity. The goal of such a platform would be to reducetime-consuming, repetitive application development tasks so thatsoftware engineers and individuals in other roles can focus ondeveloping unique, high-value features.

In order to achieve this goal, the concept of Application Platform as aService (aPaaS) is introduced, to intelligently automate workflowsthroughout the enterprise. An aPaaS system is hosted remotely from theenterprise, but may access data, applications, and services within theenterprise by way of secure connections. Such an aPaaS system may have anumber of advantageous capabilities and characteristics. Theseadvantages and characteristics may be able to improve the enterprise'soperations and workflow for IT, HR, CRM, customer service, applicationdevelopment, and security.

The aPaaS system may support development and execution ofmodel-view-controller (MVC) applications. MVC applications divide theirfunctionality into three interconnected parts (model, view, andcontroller) in order to isolate representations of information from themanner in which the information is presented to the user, therebyallowing for efficient code reuse and parallel development. Theseapplications may be web-based, and offer create, read, update, delete(CRUD) capabilities. This allows new applications to be built on acommon application infrastructure.

The aPaaS system may support standardized application components, suchas a standardized set of widgets for graphical user interface (GUI)development. In this way, applications built using the aPaaS system havea common look and feel. Other software components and modules may bestandardized as well. In some cases, this look and feel can be brandedor skinned with an enterprise's custom logos and/or color schemes.

The aPaaS system may support the ability to configure the behavior ofapplications using metadata. This allows application behaviors to berapidly adapted to meet specific needs. Such an approach reducesdevelopment time and increases flexibility. Further, the aPaaS systemmay support GUI tools that facilitate metadata creation and management,thus reducing errors in the metadata.

The aPaaS system may support clearly-defined interfaces betweenapplications, so that software developers can avoid unwantedinter-application dependencies. Thus, the aPaaS system may implement aservice layer in which persistent state information and other data isstored.

The aPaaS system may support a rich set of integration features so thatthe applications thereon can interact with legacy applications andthird-party applications. For instance, the aPaaS system may support acustom employee-onboarding system that integrates with legacy HR, IT,and accounting systems.

The aPaaS system may support enterprise-grade security. Furthermore,since the aPaaS system may be remotely hosted, it should also utilizesecurity procedures when it interacts with systems in the enterprise orthird-party networks and services hosted outside of the enterprise. Forexample, the aPaaS system may be configured to share data amongst theenterprise and other parties to detect and identify common securitythreats.

Other features, functionality, and advantages of an aPaaS system mayexist. This description is for purpose of example and is not intended tobe limiting.

As an example of the aPaaS development process, a software developer maybe tasked to create a new application using the aPaaS system. First, thedeveloper may define the data model, which specifies the types of datathat the application uses and the relationships therebetween. Then, viaa GUI of the aPaaS system, the developer enters (e.g., uploads) the datamodel. The aPaaS system automatically creates all of the correspondingdatabase tables, fields, and relationships, which can then be accessedvia an object-oriented services layer.

In addition, the aPaaS system can also build a fully-functional MVCapplication with client-side interfaces and server-side CRUD logic. Thisgenerated application may serve as the basis of further development forthe user. Advantageously, the developer does not have to spend a largeamount of time on basic application functionality. Further, since theapplication may be web-based, it can be accessed from anyInternet-enabled client device. Alternatively or additionally, a localcopy of the application may be able to be accessed, for instance, whenInternet service is not available.

The aPaaS system may also support a rich set of pre-definedfunctionality that can be added to applications. These features includesupport for searching, email, templating, workflow design, reporting,analytics, social media, scripting, mobile-friendly output, andcustomized GUIs.

The following embodiments describe architectural and functional aspectsof example aPaaS systems, as well as the features and advantagesthereof.

II. EXAMPLE COMPUTING DEVICES AND CLOUD-BASED COMPUTING ENVIRONMENTS

FIG. 1 is a simplified block diagram exemplifying a computing device100, illustrating some of the components that could be included in acomputing device arranged to operate in accordance with the embodimentsherein. Computing device 100 could be a client device (e.g., a deviceactively operated by a user), a server device (e.g., a device thatprovides computational services to client devices), or some other typeof computational platform. Some server devices may operate as clientdevices from time to time in order to perform particular operations, andsome client devices may incorporate server features.

In this example, computing device 100 includes processor 102, memory104, network interface 106, and an input/output unit 108, all of whichmay be coupled by a system bus 110 or a similar mechanism. In someembodiments, computing device 100 may include other components and/orperipheral devices (e.g., detachable storage, printers, and so on).

Processor 102 may be one or more of any type of computer processingelement, such as a central processing unit (CPU), a co-processor (e.g.,a mathematics, graphics, or encryption co-processor), a digital signalprocessor (DSP), a network processor, and/or a form of integratedcircuit or controller that performs processor operations. In some cases,processor 102 may be one or more single-core processors. In other cases,processor 102 may be one or more multi-core processors with multipleindependent processing units. Processor 102 may also include registermemory for temporarily storing instructions being executed and relateddata, as well as cache memory for temporarily storing recently-usedinstructions and data.

Memory 104 may be any form of computer-usable memory, including but notlimited to random access memory (RAM), read-only memory (ROM), andnon-volatile memory (e.g., flash memory, hard disk drives, solid statedrives, compact discs (CDs), digital video discs (DVDs), and/or tapestorage). Thus, memory 104 represents both main memory units, as well aslong-term storage. Other types of memory may include biological memory.

Memory 104 may store program instructions and/or data on which programinstructions may operate. By way of example, memory 104 may store theseprogram instructions on a non-transitory, computer-readable medium, suchthat the instructions are executable by processor 102 to carry out anyof the methods, processes, or operations disclosed in this specificationor the accompanying drawings.

As shown in FIG. 1, memory 104 may include firmware 104A, kernel 104B,and/or applications 104C. Firmware 104A may be program code used to bootor otherwise initiate some or all of computing device 100. Kernel 104Bmay be an operating system, including modules for memory management,scheduling and management of processes, input/output, and communication.Kernel 104B may also include device drivers that allow the operatingsystem to communicate with the hardware modules (e.g., memory units,networking interfaces, ports, and busses), of computing device 100.Applications 104C may be one or more user-space software programs, suchas web browsers or email clients, as well as any software libraries usedby these programs. Memory 104 may also store data used by these andother programs and applications.

Network interface 106 may take the form of one or more wirelineinterfaces, such as Ethernet (e.g., Fast Ethernet, Gigabit Ethernet, andso on). Network interface 106 may also support communication over one ormore non-Ethernet media, such as coaxial cables or power lines, or overwide-area media, such as Synchronous Optical Networking (SONET) ordigital subscriber line (DSL) technologies. Network interface 106 mayadditionally take the form of one or more wireless interfaces, such asIEEE 802.11 (Wifi), BLUETOOTH®, global positioning system (GPS), or awide-area wireless interface. However, other forms of physical layerinterfaces and other types of standard or proprietary communicationprotocols may be used over network interface 106. Furthermore, networkinterface 106 may comprise multiple physical interfaces. For instance,some embodiments of computing device 100 may include Ethernet,BLUETOOTH®, and Wifi interfaces.

Input/output unit 108 may facilitate user and peripheral deviceinteraction with computing device 100. Input/output unit 108 may includeone or more types of input devices, such as a keyboard, a mouse, a touchscreen, and so on. Similarly, input/output unit 108 may include one ormore types of output devices, such as a screen, monitor, printer, and/orone or more light emitting diodes (LEDs). Additionally or alternatively,computing device 100 may communicate with other devices using auniversal serial bus (USB) or high-definition multimedia interface(HDMI) port interface, for example.

In some embodiments, one or more computing devices like computing device100 may be deployed to support an aPaaS architecture. The exact physicallocation, connectivity, and configuration of these computing devices maybe unknown and/or unimportant to client devices. Accordingly, thecomputing devices may be referred to as “cloud-based” devices that maybe housed at various remote data center locations.

FIG. 2 depicts a cloud-based server cluster 200 in accordance withexample embodiments. In FIG. 2, operations of a computing device (e.g.,computing device 100) may be distributed between server devices 202,data storage 204, and routers 206, all of which may be connected bylocal cluster network 208. The number of server devices 202, datastorages 204, and routers 206 in server cluster 200 may depend on thecomputing task(s) and/or applications assigned to server cluster 200.

For example, server devices 202 can be configured to perform variouscomputing tasks of computing device 100. Thus, computing tasks can bedistributed among one or more of server devices 202. To the extent thatthese computing tasks can be performed in parallel, such a distributionof tasks may reduce the total time to complete these tasks and return aresult. For purpose of simplicity, both server cluster 200 andindividual server devices 202 may be referred to as a “server device.”This nomenclature should be understood to imply that one or moredistinct server devices, data storage devices, and cluster routers maybe involved in server device operations.

Data storage 204 may be data storage arrays that include drive arraycontrollers configured to manage read and write access to groups of harddisk drives and/or solid state drives. The drive array controllers,alone or in conjunction with server devices 202, may also be configuredto manage backup or redundant copies of the data stored in data storage204 to protect against drive failures or other types of failures thatprevent one or more of server devices 202 from accessing units of datastorage 204. Other types of memory aside from drives may be used.

Routers 206 may include networking equipment configured to provideinternal and external communications for server cluster 200. Forexample, routers 206 may include one or more packet-switching and/orrouting devices (including switches and/or gateways) configured toprovide (i) network communications between server devices 202 and datastorage 204 via local cluster network 208, and/or (ii) networkcommunications between the server cluster 200 and other devices viacommunication link 210 to network 212.

Additionally, the configuration of routers 206 can be based at least inpart on the data communication requirements of server devices 202 anddata storage 204, the latency and throughput of the local clusternetwork 208, the latency, throughput, and cost of communication link210, and/or other factors that may contribute to the cost, speed,fault-tolerance, resiliency, efficiency and/or other design goals of thesystem architecture.

As a possible example, data storage 204 may include any form ofdatabase, such as a structured query language (SQL) database. Varioustypes of data structures may store the information in such a database,including but not limited to tables, arrays, lists, trees, and tuples.Furthermore, any databases in data storage 204 may be monolithic ordistributed across multiple physical devices.

Server devices 202 may be configured to transmit data to and receivedata from data storage 204. This transmission and retrieval may take theform of SQL queries or other types of database queries, and the outputof such queries, respectively. Additional text, images, video, and/oraudio may be included as well. Furthermore, server devices 202 mayorganize the received data into web page representations. Such arepresentation may take the form of a markup language, such as thehypertext markup language (HTML), the extensible markup language (XML),or some other standardized or proprietary format. Moreover, serverdevices 202 may have the capability of executing various types ofcomputerized scripting languages, such as but not limited to Perl,Python, PHP Hypertext Preprocessor (PHP), Active Server Pages (ASP),JavaScript, and so on. Computer program code written in these languagesmay facilitate the providing of web pages to client devices, as well asclient device interaction with the web pages.

III. EXAMPLE REMOTE NETWORK MANAGEMENT ARCHITECTURE

FIG. 3 depicts a remote network management architecture, in accordancewith example embodiments. This architecture includes three maincomponents, managed network 300, remote network management platform 320,and third-party networks 340, all connected by way of Internet 350.

Managed network 300 may be, for example, an enterprise network used byan entity for computing and communications tasks, as well as storage ofdata. Thus, managed network 300 may include client devices 302, serverdevices 304, routers 306, virtual machines 308, firewall 310, and/orproxy servers 312. Client devices 302 may be embodied by computingdevice 100, server devices 304 may be embodied by computing device 100or server cluster 200, and routers 306 may be any type of router,switch, or gateway.

Virtual machines 308 may be embodied by one or more of computing device100 or server cluster 200. In general, a virtual machine is an emulationof a computing system, and mimics the functionality (e.g., processor,memory, and communication resources) of a physical computer. Onephysical computing system, such as server cluster 200, may support up tothousands of individual virtual machines. In some embodiments, virtualmachines 308 may be managed by a centralized server device orapplication that facilitates allocation of physical computing resourcesto individual virtual machines, as well as performance and errorreporting. Enterprises often employ virtual machines in order toallocate computing resources in an efficient, as needed fashion.Providers of virtualized computing systems include VMWARE® andMICROSOFT®.

Firewall 310 may be one or more specialized routers or server devicesthat protect managed network 300 from unauthorized attempts to accessthe devices, applications, and services therein, while allowingauthorized communication that is initiated from managed network 300.Firewall 310 may also provide intrusion detection, web filtering, virusscanning, application-layer gateways, and other applications orservices. In some embodiments not shown in FIG. 3, managed network 300may include one or more virtual private network (VPN) gateways withwhich it communicates with remote network management platform 320 (seebelow).

Managed network 300 may also include one or more proxy servers 312. Anembodiment of proxy servers 312 may be a server device that facilitatescommunication and movement of data between managed network 300, remotenetwork management platform 320, and third-party networks 340. Inparticular, proxy servers 312 may be able to establish and maintainsecure communication sessions with one or more computational instancesof remote network management platform 320. By way of such a session,remote network management platform 320 may be able to discover andmanage aspects of the architecture and configuration of managed network300 and its components. Possibly with the assistance of proxy servers312, remote network management platform 320 may also be able to discoverand manage aspects of third-party networks 340 that are used by managednetwork 300.

Firewalls, such as firewall 310, typically deny all communicationsessions that are incoming by way of Internet 350, unless such a sessionwas ultimately initiated from behind the firewall (i.e., from a deviceon managed network 300) or the firewall has been explicitly configuredto support the session. By placing proxy servers 312 behind firewall 310(e.g., within managed network 300 and protected by firewall 310), proxyservers 312 may be able to initiate these communication sessions throughfirewall 310. Thus, firewall 310 might not have to be specificallyconfigured to support incoming sessions from remote network managementplatform 320, thereby avoiding potential security risks to managednetwork 300.

In some cases, managed network 300 may consist of a few devices and asmall number of networks. In other deployments, managed network 300 mayspan multiple physical locations and include hundreds of networks andhundreds of thousands of devices. Thus, the architecture depicted inFIG. 3 is capable of scaling up or down by orders of magnitude.

Furthermore, depending on the size, architecture, and connectivity ofmanaged network 300, a varying number of proxy servers 312 may bedeployed therein. For example, each one of proxy servers 312 may beresponsible for communicating with remote network management platform320 regarding a portion of managed network 300. Alternatively oradditionally, sets of two or more proxy servers may be assigned to sucha portion of managed network 300 for purposes of load balancing,redundancy, and/or high availability.

Remote network management platform 320 is a hosted environment thatprovides aPaaS services to users, particularly to the operators ofmanaged network 300. These services may take the form of web-basedportals, for instance. Thus, a user can securely access remote networkmanagement platform 320 from, for instance, client devices 302, orpotentially from a client device outside of managed network 300. By wayof the web-based portals, users may design, test, and deployapplications, generate reports, view analytics, and perform other tasks.

As shown in FIG. 3, remote network management platform 320 includes fourcomputational instances 322, 324, 326, and 328. Each of these instancesmay represent one or more server devices and/or one or more databasesthat provide a set of web portals, services, and applications (e.g., awholly-functioning aPaaS system) available to a particular customer. Insome cases, a single customer may use multiple computational instances.For example, managed network 300 may be an enterprise customer of remotenetwork management platform 320, and may use computational instances322, 324, and 326. The reason for providing multiple instances to onecustomer is that the customer may wish to independently develop, test,and deploy its applications and services. Thus, computational instance322 may be dedicated to application development related to managednetwork 300, computational instance 324 may be dedicated to testingthese applications, and computational instance 326 may be dedicated tothe live operation of tested applications and services. A computationalinstance may also be referred to as a hosted instance, a remoteinstance, a customer instance, or by some other designation. Anyapplication deployed onto a computational instance may be a scopedapplication, in that its access to databases within the computationalinstance can be restricted to certain elements therein (e.g., one ormore particular database tables or particular rows with one or moredatabase tables).

For purpose of clarity, the disclosure herein refers to the physicalhardware, software, and arrangement thereof as a “computationalinstance.” Note that users may colloquially refer to the graphical userinterfaces provided thereby as “instances.” But unless it is definedotherwise herein, a “computational instance” is a computing systemdisposed within remote network management platform 320.

The multi-instance architecture of remote network management platform320 is in contrast to conventional multi-tenant architectures, overwhich multi-instance architectures exhibit several advantages. Inmulti-tenant architectures, data from different customers (e.g.,enterprises) are comingled in a single database. While these customers'data are separate from one another, the separation is enforced by thesoftware that operates the single database. As a consequence, a securitybreach in this system may impact all customers' data, creatingadditional risk, especially for entities subject to governmental,healthcare, and/or financial regulation. Furthermore, any databaseoperations that impact one customer will likely impact all customerssharing that database. Thus, if there is an outage due to hardware orsoftware errors, this outage affects all such customers. Likewise, ifthe database is to be upgraded to meet the needs of one customer, itwill be unavailable to all customers during the upgrade process. Often,such maintenance windows will be long, due to the size of the shareddatabase.

In contrast, the multi-instance architecture provides each customer withits own database in a dedicated computing instance. This preventscomingling of customer data, and allows each instance to beindependently managed. For example, when one customer's instanceexperiences an outage due to errors or an upgrade, other computationalinstances are not impacted. Maintenance down time is limited because thedatabase only contains one customer's data. Further, the simpler designof the multi-instance architecture allows redundant copies of eachcustomer database and instance to be deployed in a geographicallydiverse fashion. This facilitates high availability, where the liveversion of the customer's instance can be moved when faults are detectedor maintenance is being performed.

In some embodiments, remote network management platform 320 may includeone or more central instances, controlled by the entity that operatesthis platform. Like a computational instance, a central instance mayinclude some number of physical or virtual servers and database devices.Such a central instance may serve as a repository for data that can beshared amongst at least some of the computational instances. Forinstance, definitions of common security threats that could occur on thecomputational instances, software packages that are commonly discoveredon the computational instances, and/or an application store forapplications that can be deployed to the computational instances mayreside in a central instance. Computational instances may communicatewith central instances by way of well-defined interfaces in order toobtain this data.

In order to support multiple computational instances in an efficientfashion, remote network management platform 320 may implement aplurality of these instances on a single hardware platform. For example,when the aPaaS system is implemented on a server cluster such as servercluster 200, it may operate a virtual machine that dedicates varyingamounts of computational, storage, and communication resources toinstances. But full virtualization of server cluster 200 might not benecessary, and other mechanisms may be used to separate instances. Insome examples, each instance may have a dedicated account and one ormore dedicated databases on server cluster 200. Alternatively,computational instance 322 may span multiple physical devices.

In some cases, a single server cluster of remote network managementplatform 320 may support multiple independent enterprises. Furthermore,as described below, remote network management platform 320 may includemultiple server clusters deployed in geographically diverse data centersin order to facilitate load balancing, redundancy, and/or highavailability.

Third-party networks 340 may be remote server devices (e.g., a pluralityof server clusters such as server cluster 200) that can be used foroutsourced computational, data storage, communication, and servicehosting operations. These servers may be virtualized (i.e., the serversmay be virtual machines). Examples of third-party networks 340 mayinclude AMAZON WEB SERVICES® and MICROSOFT® Azure. Like remote networkmanagement platform 320, multiple server clusters supporting third-partynetworks 340 may be deployed at geographically diverse locations forpurposes of load balancing, redundancy, and/or high availability.

Managed network 300 may use one or more of third-party networks 340 todeploy applications and services to its clients and customers. Forinstance, if managed network 300 provides online music streamingservices, third-party networks 340 may store the music files and provideweb interface and streaming capabilities. In this way, the enterprise ofmanaged network 300 does not have to build and maintain its own serversfor these operations.

Remote network management platform 320 may include modules thatintegrate with third-party networks 340 to expose virtual machines andmanaged services therein to managed network 300. The modules may allowusers to request virtual resources and provide flexible reporting forthird-party networks 340. In order to establish this functionality, auser from managed network 300 might first establish an account withthird-party networks 340, and request a set of associated resources.Then, the user may enter the account information into the appropriatemodules of remote network management platform 320. These modules maythen automatically discover the manageable resources in the account, andalso provide reports related to usage, performance, and billing.

Internet 350 may represent a portion of the global Internet. However,Internet 350 may alternatively represent a different type of network,such as a private wide-area or local-area packet-switched network.

FIG. 4 further illustrates the communication environment between managednetwork 300 and computational instance 322, and introduces additionalfeatures and alternative embodiments. In FIG. 4, computational instance322 is replicated across data centers 400A and 400B. These data centersmay be geographically distant from one another, perhaps in differentcities or different countries. Each data center includes supportequipment that facilitates communication with managed network 300, aswell as remote users.

In data center 400A, network traffic to and from external devices flowseither through VPN gateway 402A or firewall 404A. VPN gateway 402A maybe peered with VPN gateway 412 of managed network 300 by way of asecurity protocol such as Internet Protocol Security (IPSEC) orTransport Layer Security (TLS). Firewall 404A may be configured to allowaccess from authorized users, such as user 414 and remote user 416, andto deny access to unauthorized users. By way of firewall 404A, theseusers may access computational instance 322, and possibly othercomputational instances. Load balancer 406A may be used to distributetraffic amongst one or more physical or virtual server devices that hostcomputational instance 322. Load balancer 406A may simplify user accessby hiding the internal configuration of data center 400A, (e.g.,computational instance 322) from client devices. For instance, ifcomputational instance 322 includes multiple physical or virtualcomputing devices that share access to multiple databases, load balancer406A may distribute network traffic and processing tasks across thesecomputing devices and databases so that no one computing device ordatabase is significantly busier than the others. In some embodiments,computational instance 322 may include VPN gateway 402A, firewall 404A,and load balancer 406A.

Data center 400B may include its own versions of the components in datacenter 400A. Thus, VPN gateway 402B, firewall 404B, and load balancer406B may perform the same or similar operations as VPN gateway 402A,firewall 404A, and load balancer 406A, respectively. Further, by way ofreal-time or near-real-time database replication and/or otheroperations, computational instance 322 may exist simultaneously in datacenters 400A and 400B.

Data centers 400A and 400B as shown in FIG. 4 may facilitate redundancyand high availability. In the configuration of FIG. 4, data center 400Ais active and data center 400B is passive. Thus, data center 400A isserving all traffic to and from managed network 300, while the versionof computational instance 322 in data center 400B is being updated innear-real-time. Other configurations, such as one in which both datacenters are active, may be supported.

Should data center 400A fail in some fashion or otherwise becomeunavailable to users, data center 400B can take over as the active datacenter. For example, domain name system (DNS) servers that associate adomain name of computational instance 322 with one or more InternetProtocol (IP) addresses of data center 400A may re-associate the domainname with one or more IP addresses of data center 400B. After thisre-association completes (which may take less than one second or severalseconds), users may access computational instance 322 by way of datacenter 400B.

FIG. 4 also illustrates a possible configuration of managed network 300.As noted above, proxy servers 312 and user 414 may access computationalinstance 322 through firewall 310. Proxy servers 312 may also accessconfiguration items 410. In FIG. 4, configuration items 410 may refer toany or all of client devices 302, server devices 304, routers 306, andvirtual machines 308, any applications or services executing thereon, aswell as relationships between devices, applications, and services. Thus,the term “configuration items” may be shorthand for any physical orvirtual device, or any application or service remotely discoverable ormanaged by computational instance 322, or relationships betweendiscovered devices, applications, and services. Configuration items maybe represented in a configuration management database (CMDB) ofcomputational instance 322.

As noted above, VPN gateway 412 may provide a dedicated VPN to VPNgateway 402A. Such a VPN may be helpful when there is a significantamount of traffic between managed network 300 and computational instance322, or security policies otherwise suggest or require use of a VPNbetween these sites. In some embodiments, any device in managed network300 and/or computational instance 322 that directly communicates via theVPN is assigned a public IP address. Other devices in managed network300 and/or computational instance 322 may be assigned private IPaddresses (e.g., IP addresses selected from the 10.0.0.0-10.255.255.255or 192.168.0.0-192.168.255.255 ranges, represented in shorthand assubnets 10.0.0.0/8 and 192.168.0.0/16, respectively).

IV. EXAMPLE DEVICE, APPLICATION, AND SERVICE DISCOVERY

In order for remote network management platform 320 to administer thedevices, applications, and services of managed network 300, remotenetwork management platform 320 may first determine what devices arepresent in managed network 300, the configurations and operationalstatuses of these devices, and the applications and services provided bythe devices, and well as the relationships between discovered devices,applications, and services. As noted above, each device, application,service, and relationship may be referred to as a configuration item.The process of defining configuration items within managed network 300is referred to as discovery, and may be facilitated at least in part byproxy servers 312.

For purpose of the embodiments herein, an “application” may refer to oneor more processes, threads, programs, client modules, server modules, orany other software that executes on a device or group of devices. A“service” may refer to a high-level capability provided by multipleapplications executing on one or more devices working in conjunctionwith one another. For example, a high-level web service may involvemultiple web application server threads executing on one device andaccessing information from a database application that executes onanother device.

FIG. 5A provides a logical depiction of how configuration items can bediscovered, as well as how information related to discoveredconfiguration items can be stored. For sake of simplicity, remotenetwork management platform 320, third-party networks 340, and Internet350 are not shown.

In FIG. 5A, CMDB 500 and task list 502 are stored within computationalinstance 322. Computational instance 322 may transmit discovery commandsto proxy servers 312. In response, proxy servers 312 may transmit probesto various devices, applications, and services in managed network 300.These devices, applications, and services may transmit responses toproxy servers 312, and proxy servers 312 may then provide informationregarding discovered configuration items to CMDB 500 for storagetherein. Configuration items stored in CMDB 500 represent theenvironment of managed network 300.

Task list 502 represents a list of activities that proxy servers 312 areto perform on behalf of computational instance 322. As discovery takesplace, task list 502 is populated. Proxy servers 312 repeatedly querytask list 502, obtain the next task therein, and perform this task untiltask list 502 is empty or another stopping condition has been reached.

To facilitate discovery, proxy servers 312 may be configured withinformation regarding one or more subnets in managed network 300 thatare reachable by way of proxy servers 312. For instance, proxy servers312 may be given the IP address range 192.168.0/24 as a subnet. Then,computational instance 322 may store this information in CMDB 500 andplace tasks in task list 502 for discovery of devices at each of theseaddresses.

FIG. 5A also depicts devices, applications, and services in managednetwork 300 as configuration items 504, 506, 508, 510, and 512. As notedabove, these configuration items represent a set of physical and/orvirtual devices (e.g., client devices, server devices, routers, orvirtual machines), applications executing thereon (e.g., web servers,email servers, databases, or storage arrays), relationshipstherebetween, as well as services that involve multiple individualconfiguration items.

Placing the tasks in task list 502 may trigger or otherwise cause proxyservers 312 to begin discovery. Alternatively or additionally, discoverymay be manually triggered or automatically triggered based on triggeringevents (e.g., discovery may automatically begin once per day at aparticular time).

In general, discovery may proceed in four logical phases: scanning,classification, identification, and exploration. Each phase of discoveryinvolves various types of probe messages being transmitted by proxyservers 312 to one or more devices in managed network 300. The responsesto these probes may be received and processed by proxy servers 312, andrepresentations thereof may be transmitted to CMDB 500. Thus, each phasecan result in more configuration items being discovered and stored inCMDB 500.

In the scanning phase, proxy servers 312 may probe each IP address inthe specified range of IP addresses for open Transmission ControlProtocol (TCP) and/or User Datagram Protocol (UDP) ports to determinethe general type of device. The presence of such open ports at an IPaddress may indicate that a particular application is operating on thedevice that is assigned the IP address, which in turn may identify theoperating system used by the device. For example, if TCP port 135 isopen, then the device is likely executing a WINDOWS® operating system.Similarly, if TCP port 22 is open, then the device is likely executing aUNIX® operating system, such as LINUX®. If UDP port 161 is open, thenthe device may be able to be further identified through the SimpleNetwork Management Protocol (SNMP). Other possibilities exist. Once thepresence of a device at a particular IP address and its open ports havebeen discovered, these configuration items are saved in CMDB 500.

In the classification phase, proxy servers 312 may further probe eachdiscovered device to determine the version of its operating system. Theprobes used for a particular device are based on information gatheredabout the devices during the scanning phase. For example, if a device isfound with TCP port 22 open, a set of UNIX®-specific probes may be used.Likewise, if a device is found with TCP port 135 open, a set ofWINDOWS®-specific probes may be used. For either case, an appropriateset of tasks may be placed in task list 502 for proxy servers 312 tocarry out. These tasks may result in proxy servers 312 logging on, orotherwise accessing information from the particular device. Forinstance, if TCP port 22 is open, proxy servers 312 may be instructed toinitiate a Secure Shell (SSH) connection to the particular device andobtain information about the operating system thereon from particularlocations in the file system. Based on this information, the operatingsystem may be determined. As an example, a UNIX® device with TCP port 22open may be classified as AIX®, HPUX, LINUX®, MACOS®, or SOLARIS®. Thisclassification information may be stored as one or more configurationitems in CMDB 500.

In the identification phase, proxy servers 312 may determine specificdetails about a classified device. The probes used during this phase maybe based on information gathered about the particular devices during theclassification phase. For example, if a device was classified as LINUX®,a set of LINUX®-specific probes may be used. Likewise if a device wasclassified as WINDOWS® 2012, as a set of WINDOWS®-2012-specific probesmay be used. As was the case for the classification phase, anappropriate set of tasks may be placed in task list 502 for proxyservers 312 to carry out. These tasks may result in proxy servers 312reading information from the particular device, such as basicinput/output system (BIOS) information, serial numbers, networkinterface information, media access control address(es) assigned tothese network interface(s), IP address(es) used by the particular deviceand so on. This identification information may be stored as one or moreconfiguration items in CMDB 500.

In the exploration phase, proxy servers 312 may determine furtherdetails about the operational state of a classified device. The probesused during this phase may be based on information gathered about theparticular devices during the classification phase and/or theidentification phase. Again, an appropriate set of tasks may be placedin task list 502 for proxy servers 312 to carry out. These tasks mayresult in proxy servers 312 reading additional information from theparticular device, such as processor information, memory information,lists of running processes (applications), and so on. Once more, thediscovered information may be stored as one or more configuration itemsin CMDB 500.

Running discovery on a network device, such as a router, may utilizeSNMP. Instead of or in addition to determining a list of runningprocesses or other application-related information, discovery maydetermine additional subnets known to the router and the operationalstate of the router's network interfaces (e.g., active, inactive, queuelength, number of packets dropped, etc.). The IP addresses of theadditional subnets may be candidates for further discovery procedures.Thus, discovery may progress iteratively or recursively.

Once discovery completes, a snapshot representation of each discovereddevice, application, and service is available in CMDB 500. For example,after discovery, operating system version, hardware configuration andnetwork configuration details for client devices, server devices, androuters in managed network 300, as well as applications executingthereon, may be stored. This collected information may be presented to auser in various ways to allow the user to view the hardware compositionand operational status of devices, as well as the characteristics ofservices that span multiple devices and applications.

Furthermore, CMDB 500 may include entries regarding dependencies andrelationships between configuration items. More specifically, anapplication that is executing on a particular server device, as well asthe services that rely on this application, may be represented as suchin CMDB 500. For instance, suppose that a database application isexecuting on a server device, and that this database application is usedby a new employee onboarding service as well as a payroll service. Thus,if the server device is taken out of operation for maintenance, it isclear that the employee onboarding service and payroll service will beimpacted. Likewise, the dependencies and relationships betweenconfiguration items may be able to represent the services impacted whena particular router fails.

In general, dependencies and relationships between configuration itemsmay be displayed on a web-based interface and represented in ahierarchical fashion. Thus, adding, changing, or removing suchdependencies and relationships may be accomplished by way of thisinterface.

Furthermore, users from managed network 300 may develop workflows thatallow certain coordinated activities to take place across multiplediscovered devices. For instance, an IT workflow might allow the user tochange the common administrator password to all discovered LINUX®devices in single operation.

In order for discovery to take place in the manner described above,proxy servers 312, CMDB 500, and/or one or more credential stores may beconfigured with credentials for one or more of the devices to bediscovered. Credentials may include any type of information needed inorder to access the devices. These may include userid/password pairs,certificates, and so on. In some embodiments, these credentials may bestored in encrypted fields of CMDB 500. Proxy servers 312 may containthe decryption key for the credentials so that proxy servers 312 can usethese credentials to log on to or otherwise access devices beingdiscovered.

The discovery process is depicted as a flow chart in FIG. 5B. At block520, the task list in the computational instance is populated, forinstance, with a range of IP addresses. At block 522, the scanning phasetakes place. Thus, the proxy servers probe the IP addresses for devicesusing these IP addresses, and attempt to determine the operating systemsthat are executing on these devices. At block 524, the classificationphase takes place. The proxy servers attempt to determine the operatingsystem version of the discovered devices. At block 526, theidentification phase takes place. The proxy servers attempt to determinethe hardware and/or software configuration of the discovered devices. Atblock 528, the exploration phase takes place. The proxy servers attemptto determine the operational state and applications executing on thediscovered devices. At block 530, further editing of the configurationitems representing the discovered devices and applications may takeplace. This editing may be automated and/or manual in nature.

The blocks represented in FIG. 5B are for purpose of example. Discoverymay be a highly configurable procedure that can have more or fewerphases, and the operations of each phase may vary. In some cases, one ormore phases may be customized, or may otherwise deviate from theexemplary descriptions above.

V. EXAMPLE PERFORMANCE ANALYTICS VISUALIZATIONS

As described herein, a visualization may take various forms and be madeup of one or more of various “PA elements” or “PA entities.” Generally,visualizations typically involve the presentation of KPIs in a graphicalformat. The term PA entity is used herein to describe both a specific orgeneral graphical function or operation, as well as a PA function,operation, or definition. For example, a widget may describe a graphicalcomponent configured for displaying a data plot and providing graphicalor textual control elements for allowing a user to adjust appearance,data range, etc., of a KPI display. As another example, a breakdown maybe a definable filter that can be applied to measurement data, and mayhave one or more associated graphical elements for creating andadjusting breakdown parameters (breakdowns are discussed in more detailbelow). These are just two examples. Other, non-limiting examples of PAentities include dashboards, tabs, scorecards, and databases.

KPIs, which, as noted, may themselves be considered PA entities, mayalso be referred to as metrics or indicators. In general, KPIs are atype of performance measurement used to evaluate current and pastconditions, as well as to forecast trends. KPIs can be used to evaluatethe success of a particular activity, such as making progress towardstrategic goals or the repeated achievement of some level of operationalgoal (for example, zero defects, a mean time to resolution of less than24 hours for certain types of IT issues, or less than 70% processorutilization on a particular server device). KPIs can also be used tomeasure and/or track an organization's mission. In this context, KPIcould be associated with sales, inventory, or other mission-relatedperformance measures.

The act of measuring a KPI may be referred to as collection. KPIs areassociated with one or more KPI sources that define one or more fieldsin a database table (sometimes called a facts table) that are to becollected in order to provide the KPI data. KPI sources may also specifyfilters to include only a subset of the information in a field. KPIdata—e.g., measured or collected data—may be stored, possibly with otherKPI-related and PA-related data, in the database. The database for thesedata is referred to herein as a PA database.

Data measurements associated with a KPI are also referred to herein as“scores.” With this terminology, a KPI—either as a PA operational entityor as a graphical operational entity—may also be considered as adescriptor or specification of an indicator, while the correspondingscores are actual measurements collected as specified by the descriptor.For example, a KPI may be defined or created for tracking processorutilization on a particular server. The KPI may also define time windowsfor data collection and frequency of measurements during the timewindows, as well as possibly other filters that may be applied duringdata collection. The scores for the KPI may then be the utilizationmeasurements collected during the specified time windows at thespecified collection or measurement frequencies. The scores may then becollected in records in the PA database. This is just one non-limiting,and simple, example of KPI scores. Other, more complicated KPIdefinitions and scores are possible as well. As described below, scoresmay be collected and displayed in scorecards.

A dashboard is single-screen GUI component that contains one or moretabs that logically group components that generally belong together. Insome embodiments, a dashboard may be equivalent to or contained within aGUI window. Tabs may be graphical control elements that allow multipledocuments or panels to be contained within a single dashboard. Tabs canbe used to switch between such documents or panels. Individual GUIwidgets may be present on such tabs. In the context of PA, these widgetsmay display a KPI as a latest value, a time series, in a chart, in aspeedometer, in a dial, in a scorecard, or in a column. Other variationsare possible.

Breakdowns are PA entities that allow organization and filtering of KPIdata on tabs and dashboards. Thus, breakdowns apply organization and/orfiltering to KPI score data—i.e., after KPI data (scores) have alreadybeen collected. This may be distinguished from filters and othercollection criteria defined as part of a KPI and applied as part of, orduring, data collection. In some embodiments, breakdowns may take theform of a drop down GUI widget. Regardless, the KPI data can be dividedin various ways based on category. For instance, IT trouble ticketincidents can be divided by priority or by originating department. Insome cases, breakdowns can use these multiple ways of dividing data intandem, such as breaking down IT trouble ticket incidents first bypriority, then by originating department.

A scorecard can be a dashboard, tab, or widget that displays datarelated to a single KPI (e.g., in a time series chart widget) andenables detailed analysis of this data. In some embodiments, each KPImay have an associated scorecard that is automatically created. The datamay be viewed by breakdown and/or in aggregate (e.g., counts, sums, andmaximums of the values). Scorecards may also provide ways of viewing thedatabase fields on which the KPI values are based.

Any of these elements or entities (dashboards, tabs, widgets,breakdowns, and scorecards) may be considered a visualization, orcomponents thereof, and can be user customized. For instance, a user canrearrange the tabs of a dashboard, add or remove widgets from a tab, andcreate new breakdowns. The appearance of a dashboard, such as what tabsand/or widgets are included, what formats of visualization are included,data ranges, etc., may be determined by one or more configurationsettings. In some example embodiments, configuration settings, or just“configuration” for short, may be defined by various data elements andentities, including data tables, data records, variables, parameters,and the like, which can be stored in memory and used to control thecontent and appearance of the visual, analytical, and interactivecomponents that make up a dashboard. Setting and adjusting values of thedata elements and entities allows the appearance and function thedashboard to be set up, as well as adjusted or tuned.

Example dashboards are shown in FIGS. 6A and 6B. Dashboard 600 of FIG.6A includes multiple tabs 602, such as an “Incident KPIs” tab, a “Tieranalysis” tab, and so on. The “Incident KPIs” tab is displayed, andincludes a widget in the form of a bar chart 604, titled “Open incidentsby age”. Bar chart 604 plots, for each day of an approximatelythree-month time period, the total number of open incidents for the ageranges of 0-1 days, 1-5 days, 6-30 days, 31-90 days, and over 90 days.These age ranges may be defined by the “Age” category of breakdown 606.

These incidents may be, for example, trouble tickets or help requestsopened with an IT organization. Each incident may therefore involve aparticular problem that a user has experienced, such as a computercrashing, a user being unable to log on to a service, slow performanceof a service, a request for new equipment, and so on. The ITorganization may track its performance by measuring how long it takes toresolve the incidents. For example, bar chart 604 suggests that therewere fewer open incidents near the end of the time frame than at themiddle of the time frame, but that the incidents near the end of thetime frame had remained open for a longer duration (i.e., there weremore open incidents in the 31-90 days age range).

Dashboard 600 may also include section 608, which includes three widgetsfor: the extent of the open incident backlog (in this case, there are422 open incidents currently), the first call resolution rate (in thiscase, 83.6%), and a seven-day running average of the mean time for anincident to be resolved (in this case, 3.08 days). This latter KPI mayalso be referred to mean time to resolution, or MTTR.

Dashboard 610 of FIG. 6B shows different example visualizations relatedto open incidents. This dashboard contains the same tabs 602, butincludes charts 612 and 614 instead of bar chart 604 and section 608.Chart 612 plots, for the same time frame of the visualization in FIG.6A, open incidents against the average age of these open incidents on adual y-axis graph. Chart 614 also plots open incidents, but includesrepresentations of the age distribution of these incidents.

Dashboards 600 and 610 also include various selectors, such asbreakdowns in the form of drop down menus that allow the user to viewthese KPIs in different ways. Regardless of their exact mechanisms,these dashboards allow the user to rapidly determine the status of theorganization's incident response KPIs through the use of visualizationsthat combine these KPIs.

The data displayed in bar chart 604, section 608, chart 610, and chart612 may be visualizations defined by a data model. Thus, informationdefining these visualizations may be stored in a database according tothat data model. The information may also be identified as representingone or more KPIs, and each KPI may be represented as one or more tablesin the data model. As demonstrated in FIGS. 6A and 6B, multiplevisualizations may use the same KPIs to provide different views of therepresented data.

VI. DEPENDENCY ASSESSMENT OF PA ENTITIES

In general, the potential number of KPIs for an enterprise or otherorganization can be quite large, numbering in the 100s to tens of1,000s. In practice, KPIs can be highly interrelated and connected, suchthat data feeding a metric for one KPI may be the output data fromanother KPI or multiple other KPIs. For example, a KPI metric relatingto number of overdue budget reports may directly affect a KPI measuringpercent of expenses spent on late fees which in turn may directly affecta KPI measuring yearly operating expenses. Consequently, relationshipsbetween KPIs and between PA entities can be complicated.

As a further illustration of the relationships between KPIs and other PAentities, consider the example of changing the output data type of afirst KPI, such as seconds to minutes. Such a change could cause anerror to a second KPI that uses such data as input, which maysubsequently affect a dashboard that uses the second KPI. In a largeenterprise, it may be difficult for a user or administrator to identifyhow user changes directly affect KPIs and associated PA entities ifrelationships between KPIs are undefined or unknown.

Yet, as described above, PA entities may be modified or updated fromtime to time as a matter of routine practice. For example, new versionsmay be released to update capabilities. In addition, PA entities may bemodified by a user or administrator in order to customize KPIvisualizations, as described above. There may be other reasons or causesfor modifying PA entities, as well. Considering the functionalrelationships of the various types of PA entities—e.g. tabs indashboards, widgets in tabs, KPI settings, and multiple types of datacollected—it may be expected that some of the types of modifications toa PA entity can have the potential to impact stability and/or validityof the behavior of other PA entities. Accordingly, functionaldependencies between PA entities need to be taken into account when oneor more PA entities are modified. In a system having a large number andtype of PA entities, the possible number and complexity of functionaldependencies between PA entities may therefore present a challenge tothe ability to support user and/or administrator modification to PAentities and KPI visualization within a PA system.

Still further, a user of a PA system program may want to adjust adatabase table or entries within a table that are relied on for KPI datacollection in order to change how a particular KPI is measured. In othercases, a user may want to refine conditions or apply data filters tomodify the subset of information for a particular KPI.

Example embodiments herein provide systems and methods for avoidingerrors that might otherwise occur as a result of modifying PAentities—errors that could cause the KPI and/or any associatedperformance analytics (PA) entities to fail. More particularly,identification of interrelationships and dependencies between KPIs forPA operation may be extended for mapping of functionalinterrelationships and dependencies between PA entities.

In the context of an organization's mission, for example, it is known touse KPIs to evaluate strategy and measure how well performance istracking goals. Interrelationships and dependencies betweenmission-oriented KPIs may also help assess how adjustments to goals orresults in one area may impact another. One technique for quantifyingdependencies among KPIs is to construct a “KPI tree.” As describedherein, a KPI tree is a hierarchical graph structure used by anenterprise or other organization to manage KPIs. KPI trees group KPIsinto specific target areas, which in turn may be grouped more broadorganizational themes. Within such a tree structure, an organization canidentify how KPIs affect one another, as well as how they directlyaffect overall goals. A variety of tree structures may be created toaddress different organizational needs.

In accordance with example embodiments, KPIs may be used with a PAsystem to track a variety of aspects of network operations and overallperformance of a managed network, such as network 300. Also inaccordance with example embodiments, the PA system may include a KPItree to quantify and describe interrelationships and dependenciesbetween KPIs of the PA system. The KPI tree may thus provide theframework for evaluating how different functional elements of a networkare operationally connected in terms of performance. This aspect of aKPI tree may largely follow conventional usage. Harnessing thehierarchical representation of a KPI tree in the context of a PA systemthus provides a versatile way of monitoring and managing networkperformance.

The inventors have recognized that, beyond its conventional usage, a KPItree, by its nature, incorporates mappings of many of the very types offunctional interrelationships and dependencies between PA entities thatpose challenges to management of changes and revisions of PA entitiesdescribed above. That is, the same KPI tree (or trees) used to supporttracking and monitoring of network performance and operations via KPIsin a PA system can be used—possibly with some extensions orenhancements—for real-time assessment of the impact of changes to PAentities on functional performance of the PA system itself. Thus, usinga KPI tree to map functional dependencies between PA entities may helpmake updating and/or customization of PA entities more robust againstdependency-related errors, while ensuring predictable functionaloutcomes of such changes. As such, users and/or administrators may makechanges to PA entities without having to directly or explicitly navigatethe complexities of the functional dependencies.

In accordance with example embodiments, dependencies between PA entitiesof a PA system may be represented graphically as a “dependencyassessment tree,” which may be derived from a KPI tree. The dependencyassessment tree may present a graphical representation of dependencymappings between PA entities, and may further include GUI-basedinteractions and controls for graphically exploring the hierarchy ofdependencies among user-selected PA entities and assessing the effect ofmodifications to PA entities in the tree. Graphical controls may includeinteractive functions, such as drop-down menus, point-and-clickselection, and editing actions, for graphically displaying dependenciesand graphically identifying how changes to PA entities may ripple acrossdependencies.

In further accordance with example embodiments, graphical representationmay account for a possibly limited screen size of computing devices usedby users to review configuration item information. More particularly, astreamlined layout may be used that hides portions of mappings, but nothiding indications of hidden portions. Thus, a user may be made aware ofnon-displayed portions of a larger dependency mapping, and given theoption to explore them.

FIG. 7 illustrates an example dependency assessment tree 700. Dependencyassessment tree 700 includes nodes, which represent vertices in thetree, and branches, which represent edges between the nodes. In exampleembodiments, a node on dependency assessment tree 700 corresponds to aPA entity of a PA system. For example, dependency tree 700 may includetop level node 702, which represents an incident dashboard similar tothat of dashboard 600. Below top level node 702, second level nodes 704are shown and may represent tabs similar to the multiple tabs 704 thatare displayed in dashboard 600. Accordingly, the hierarchical structureof branches in dependency assessment tree 700 can be used to indicatehow an incident dashboard relies on tabs during operation. In theexample embodiments, a level may refer to how many branches a group ofnodes are located from a root node of a tree. As such, higher levelnodes on dependency assessment tree 700 may represent more expansiveperformance analytics entities whereas lower level nodes may representsmaller entities that are typically contained within the larger entity.Thus, a given level of the dependency assessment tree 700 may becontained within a PA entity that exists above the level above, and PAentities at the given level of dependency assessment tree 700 maycontain entities in the level below the given level.

For purposes of the discussion herein, and consistent with descriptionsof example embodiments, if a first PA entity depends on any second PAentity second PA entity, the first PA entity is referred to as a parentand the second PA entity is referred to as a child. Note that a parentPA entity may have multiple children that it depends on. For example,process KPI node 706 may have multiple children that it depends duringits own operation. These dependencies can be seen third level nodes 708displayed below second level nodes 704. Thus, third level nodes 708 arethe children of process KPI node 706 and process KPI node 706 is thechild of top level node 702.

In example embodiments, dependency assessment tree 700 may be configuredto display only a limited portion or segment of the entire dependencyassessment tree based on user actions. A limited portion of a largerdependency assessment tree may be referred to as a tree view. Forinstance, if a user is only concerned with process KPIs, the user mayclick on process KPIs node 706 to filter out the branches extending fromthe remaining second level nodes 704. Dependency assessment tree 700 maybe configured allow filtering to be applied to any node on any level ofthe tree in order to obtain a desired tree view. Tree view configurationallows the dependency assessment tree 700 to be displayed to users withlimited screen size without unduly crowding the graphical userinterface. Additionally, dependency assessment tree 700 may beconfigured have a default tree view display. For example, when firstaccessing dependency assessment tree 700, a user may only see a treeview with top level node 702 and second level nodes 704.

In some usage scenarios, a parent PA entity may contain a large numberof children nodes, as seen by way of example in third level nodes 708.Instead of overcrowding the GUI with a wide display of all childrennodes for a given parent, dependency assessment tree 700 may beconfigured to only display a smaller number of children to a user andgroup the remaining child nodes into a single, expandable node, as seenby the expandable node 710, labeled “more.” The expandable node may beconfigured to display the number of child nodes that are hidden from theview. To access these hidden nodes, a user could click on expandablenode 710 to reveal a list of the hidden children nodes.

When presenting a dependency assessment tree to user, a PA system mayfurther be configured to correlate dependency assessment tree nodes andgeneral performance analytics types. For example, performance analyticstypes may include tabs, formula indicators, breakdowns, or dashboards.Other types may also be available. Thus, a PA system may create anddisplay a legend to associate a performance analytics type with a nodeon the dependency tree via a UI icon. For example, legend 712 may bedisplayed alongside dependency tree 700. Each node in dependency tree700 may have an icon that is associated with a piece of text on legend712 to enable a user to easily identify performance analytics types. Inexample embodiments, causing a cursor to hover over, or click on, a nodein dependency tree 700 may cause the node's performance analytics typemay be highlighted in legend 712.

To allow a user to quickly identify KPI dependency relationships, theexample embodiment may display a dependency path in response toselection of a node. For instance, clicking a cursor or otherinteractive selection graphic on node 706, a path through tree branchesor edges on dependency assessment tree 700 may be highlighted to displaythe higher level nodes 702 that depend on node 706. Subsequently, a usermay click on nodes 714 and 716 to further extend the dependency paththrough dependency tree 700. Thus, if a user was considering modifyingdata source feeding into node 716, they can quickly identify a chain ofpotential nodes and performance analytics entities that may be affectedby the change.

Dependency assessment tree 700 may also configure clickable icons onnodes to provide users with easy information access and interactiveoptions for the associated PA entity. For example, options menu 718 maybe displayed when a user clicks or hovers over node 714. A user may beable to view a summary on a PA entity associated with node 716 via theinfo icon alongside the options menu 718, edit the configuration of thePA entity with the “Edit” option, show the scorecard of the PA entitywith the “Show Scorecard” option, or display what node 716 is “Used for”on dependency assessment tree 700. In the illustrated example, the “Usedfor” option may display a bottom-up tree view, as described below. Otherinteractive options and action may also be included in dependencyassessment functions and operations.

In accordance with example embodiments, a PA system may be configured toupdate a dependency assessment tree in real time. For example, if adatabase that is an indicator source goes down due to a power outage, adependency assessment tree may display an error message on all nodesrepresenting PA entities that are affected by the database error. Inanother example, if a PA entity is removed from the PA system, thedeletion may be reflected in the dependency tree immediately by removingthe associated node from the dependency assessment tree. In someembodiments, the current tree view of a dependency assessment tree maybe persistent. If a user decides to navigate away from the dependencyassessment tree and then returns back, the dependency assessment treewould display the same tree view that the user left when navigatingaway.

Also in accordance with example embodiments, a PA system may provideaccess to a dependency assessment tree 700 via a client device, such asclient device 302, through a variety of methods available to a user ofthe client device. In some usage scenarios, the dependency assessmenttree may be launched as an individual application via a link on acontext menu or dashboard record. In other scenarios, the dependencytree may be part of an administrative console, for example as a defaulttab or web page, for example.

In other usage scenarios, the dependency assessment tree may be a partof a display tab when a new performance analytics indicator is createdby a user, as illustrated by way of example in FIG. 8. In exampleoperation, a user may click on impact analysis tab 802 to directlyidentify dependencies of a new indicator 804 in an indicator tree 800.In the example embodiments, a user can visually identify all breakdowns,indicators sources, and jobs that may be associated with the newindicator 804 by clicking or selecting appropriate functions orgraphical buttons (e.g., impact analysis tab 802). In an example usagescenario, the dependency assessment tree may be limited in scope to theindicator and any nodes that the indicator depends on and features forselecting other nodes may be disabled.

In further accordance with example embodiments, a dependency assessmenttree may be configured to display multiple types of tree views in theGUI of a client device. One type of view is a “top-down” tree view, asillustrated by indicator tree 800 in FIG. 8. A top-down tree view mayshow components of a PA entity in a hierarchical view with the PA entityat the top of the hierarchy. For example, if a user launches dependencyassessment tree for a dashboard, the top-down tree view may show nodesfor each of the dashboard tabs. If a user selects a dashboard tab, thetree view may then expand to show nodes that represent each of thewidgets on the dashboard. Thus, in example operation, a top-down view ofa PA entity may be generated in response to a GUI-based selection of thePA entity. An example of such a GUI-based selection is single- ordouble-clicking on the PA entity.

A dependency assessment tree may also contain a “bottom-up” tree view,as illustrated by dependency tree 900 for the PA entity 904 in FIG. 9. Abottom-up tree view may display how a node corresponding to a PA entityis being used by other nodes on the dependency assessment tree. Forexample, the PA entity 904 is a dependent node of PA entities 902; thatis, each of the PA entities 902 depends on—or uses—the PA entity 904. Itmay therefore be immediately assessed from the dependency tree 900 thata modification to the PA entity 904 may affect or impact operation ofany or all of the PA entities 902. As also illustrated in FIG. 9, theright-most node of PA entities 902 indicates 19 additional nodes thatare hidden from the current view. This illustrates an example of hiddennodes.

In further accordance with example embodiments, a GUI of a client devicemay generate a bottom-up view in response to a particular cursor-basedselection and/or option. For example, returning to FIG. 7, a user mayhover a cursor over a PA entity 716, click to access a drop-down menu,and then select an option, such as the “Used for” option illustrated inthe option drop-down menu 718. In response, a bottom-up tree view 900may be generated for the PA entity 716 (relabeled in FIG. 9 as PA entity904).

In the example embodiments, a dependency assessment tree may provide anundo button to revert back to the previous tree view. For instance,clicking on undo button 908 would result in returning to tree view 700.In addition, a dependency assessment tree may provide a reset button 901to return the tree view to a predefined starting point, such as a thefirst level parent 702 and its immediate child nodes 704 as shown inFIG. 7.

FIGS. 10A and 10B further illustrate examples of top-down and bottom-uptree views that may result from user interactions with, by way ofexample, PA entity 906. For instance, if a user directly clicks onincidents resolved node 1006, a top-down tree view 1000 may be displayedshowing every PA entity that incident resolved node 1006 may need tooperate. If a user navigates to the options menu of incidents resolvednode 906 and clicks on “Used for,” a bottom-up tree view 1002 may bedisplayed to show all instances where the node is used by other PAentities on the PA system.

The above examples illustrate only a few possible usage scenarios of adependency assessment tree of a PA system. It will be appreciated thatexample embodiments of a dependency assessment tree for PA entities mayaccommodate other usage as well.

VII. EXAMPLE OPERATIONS

FIG. 11 is a flow chart illustrating an example embodiment of a method1100 for configuring a performance analytics (PA) system, in particularby using a dependency assessment tree. The method illustrated by FIG. 11may be carried out by a computing device, such as computing device 100,and/or a cluster of computing devices, such as server cluster 200.However, the process can be carried out by other types of devices ordevice subsystems. For example, the process could be carried out by aportable computer, such as a laptop or a tablet device. In an exampleembodiment, the method illustrated in FIG. 11 may be carried out by acomputing device disposed within a computational instance, such asinstance 322, of a remote network management platform, such as platform320, which remotely manages a managed network, such as network 300.Further, the computing device may be operational to execute a PAsoftware application.

In example embodiments, the example method 1100 may be implemented by adependency assessment program executing or executable on a computingdevice. As described, the example method 1100 may include actions andoperations carried out by a computing device, some of which involveproviding information to a client device or receiving information fromthe client device. As such, some of these actions and operations mayhave corresponding actions and operations carried out by the clientdevice. For example, the client device may display certain graphicalrepresentations in a graphical user interface (GUI), based oninformation transmitted or supplied by the computing device. Similarly,some information received by the computing device from the client devicemay originate from user input at the GUI of the client device. Somethese corresponding actions and operations of the client device may thusbe considered part of one or more methods corresponding to the examplemethod 1100, and carried out in the client device.

The embodiments of FIG. 11 may be simplified by the removal of any oneor more of the features shown therein. Further, these embodiments may becombined with features, aspects, and/or implementations of any of theprevious figures or otherwise described herein.

In accordance with example embodiments, the computing device that isconfigured to carry out the example method 1100 may be part of a PAsystem that also includes a database containing a plurality of PA entityrecords. Each PA entity record may include data for configuring agraphical representation of a respective PA entity on a graphical userinterface (GUI) within the managed network, such as a GUI on a clientdevice in the managed network. In further accordance with exampleembodiments, the respective PA entity may be a component of the PAsystem configured for processing one or more key performance indicators(KPIs) of the managed network, and may be implemented as at least one ofa software component or a hardware system. Non-limiting examples of a PAentity include a KPI, a dashboard, a dashboard tab, a scorecard, awidget, a breakdown, or a database. Each PA entity record may furtherinclude information specifying a logical location of the respective PAentity in a dependency assessment tree. The dependency assessment treemay take the form of nodes and branches or edges. More particular,respective nodes may correspond to the respective PA entities of theplurality of PA entity records, and branches may connect nodes of PAentities between which there is a functional dependence.

Block 1102 may involve transmitting to a client device information fordisplaying in a GUI of the client device a graphical representation ofone or more respective PA entities. As described above, the respectivePA entities are associated with PA entity records of the database, eachof which includes data for configuring the graphical representation of arespective PA entity. In a corresponding action, the client device maydisplay the graphical representation of the one or more respective PAentities. FIG. 7 illustrates an example of one such display.

Block 1104 may involve receiving from the client device a first requestfor dependency information for a first PA entity from among the one ormore respective PA entities. For example, referring again to FIGS. 7 and9, and considering a corresponding action by the client device, aselection of the “Used for” option of the drop-down menu 718 may bereceived by the computing device as a request for the bottom-up treeview 900.

Finally, block 1106 may involve responding to the first request bytransmitting to the client device a graphical representation of a firstportion of the dependency assessment tree depicting the first PA entityand one or more dependency nodes. Here, dependency nodes are nodescorresponding to PA entities having a functional dependency relationshipwith the first PA entity. The first portion of the dependency tree mayalso include connecting branches between the dependency nodes. Forexample, referring once more to the example of FIGS. 7 and 9, the firstportion the dependency assessment tree could correspond to the bottom-uptree view 900, and the corresponding action of the client device uponreceiving the transmitted graphical representation could be to generatethe bottom-up tree view 900 in the GUI.

In accordance with example embodiments, the method may further entailreceiving from the client device a second request for dependencyinformation for a second PA entity from among the one or more dependencynodes depicted in the first portion of the dependency assessment tree.In response to the second request, the computing device may transmit tothe client device a graphical representation of a second portion of thedependency assessment tree depicting the second PA entity and one ormore dependency nodes. In this instance, the dependency nodes maycorrespond to PA entities having a functional dependency relationshipwith the second PA entity. The second portion of the dependencyassessment try may again include connecting branches between thedependency nodes. For example, considering the bottom-up tree view 900to be the first portion of the dependency assessment tree transmitted bythe computing device at block 1106, the PA entity 906 can be taken as anexample of the second PA entity, and the second request could be fordependency information relating to the PA entity 906. The response tothis second request could then be a graphical representation of thetop-down tree view 1000 illustrated in FIG. 10A, which would correspondto the second portion of the dependency assessment tree in this example.Once more, the corresponding action by the client device would be togenerate the top-down tree view 1000.

In accordance with example embodiments, and more generally, therespective nodes of the dependency assessment tree may be arranged in ahierarchy of dependency levels. In particular, the one or moredependency with dependency relationships with the first PA entity mayconsist of one or more nodes at one or more dependency levels below thatof the first PA entity, one or more nodes at one or more dependencylevels above that of the first PA entity, or a combination of both.

In further accordance with example embodiments, each of the one or morenodes at the one or more dependency levels below that of the first PAentity may correspond to a PA entity that the first PA entityfunctionally depends on, either directly or via one or more PA entitiesat one or more intervening dependency levels. In this case, the firstrequest for dependency information may be a request for identificationof the one or more nodes at the one or more dependency levels below thatof the first PA entity. The first portion of the dependency assessmenttree may then correspond to a top-down view of the first PA entity.

In further accordance with example embodiments, each of the one or morenodes at the one or more dependency levels above that of the first PAentity may correspond to a PA entity that functionally depends on thefirst PA, either directly or via one or more PA entities at one or moreintervening dependency levels. In this case, the first request fordependency information may be a request for identification of the one ormore nodes at the one or more dependency levels above that of the firstPA entity. The first portion of the dependency assessment tree may thencorrespond to a bottom-up view of the first PA entity.

In accordance with example embodiments, the dependency assessment treemay be derived from a KPI tree of KPIs of the managed network. Thus, asdescribed above, a KPI tree constructed or created for the purpose ofsupported evaluation and analysis of KPIs in a PA system may be extendedto map functional dependencies between PA entities of the PA system.

In further accordance with example embodiments, the example method 1100may further entail receiving from the client device an update messagespecifying a change to the first PA entity. Based on the specifiedchange to the first PA entity functionally, the dependency assessmentprogram may determine from among all respective PA entities that arefunctionally dependent on the first PA entity a conflict set of PAentities for which the specified change would result in erroneousoperation of zero or more. Note that the conflict set may be empty if noerroneous operation would result from the change. A graphicalrepresentation of the conflict set may then be transmitted to the clientdevice. In corresponding actions, the client device may provide GUIfunctionality for editing or changing PA entities. The dependencyassessment program may evaluate changes to determine the conflict set.The client device may the display conflict set upon receiving thegraphical representation from the computing device.

In accordance with example embodiments, the dependency assessment treemay further include a legend that contains a plurality of mappingsbetween visual icons and performance analytics types of the respectivePA entities. Corresponding actions or operations carried out by theclient device may then include displaying the graphical representationof the first portion of the dependency assessment tree together with agraphical a visual icon of the legend in each of the displayed PAentities.

Other corresponding actions or operations carried out by the clientdevice may then include display of a graphical drop-down menu ofoperations that can be applied to a given PA entity of a given one ofthe dependency nodes in response to a visual cursor hovering over agraphical representation of the given one of the dependency nodes. Thisis just one example of interactive commands or actions that may becarried at the client device as part of the dependency assessmentprogram.

VIII. CONCLUSION

The present disclosure is not to be limited in terms of the particularembodiments described in this application, which are intended asillustrations of various aspects. Many modifications and variations canbe made without departing from its scope, as will be apparent to thoseskilled in the art. Functionally equivalent methods and apparatuseswithin the scope of the disclosure, in addition to those describedherein, will be apparent to those skilled in the art from the foregoingdescriptions. Such modifications and variations are intended to fallwithin the scope of the appended claims.

The above detailed description describes various features and operationsof the disclosed systems, devices, and methods with reference to theaccompanying figures. The example embodiments described herein and inthe figures are not meant to be limiting. Other embodiments can beutilized, and other changes can be made, without departing from thescope of the subject matter presented herein. It will be readilyunderstood that the aspects of the present disclosure, as generallydescribed herein, and illustrated in the figures, can be arranged,substituted, combined, separated, and designed in a wide variety ofdifferent configurations.

With respect to any or all of the message flow diagrams, scenarios, andflow charts in the figures and as discussed herein, each step, block,and/or communication can represent a processing of information and/or atransmission of information in accordance with example embodiments.Alternative embodiments are included within the scope of these exampleembodiments. In these alternative embodiments, for example, operationsdescribed as steps, blocks, transmissions, communications, requests,responses, and/or messages can be executed out of order from that shownor discussed, including substantially concurrently or in reverse order,depending on the functionality involved. Further, more or fewer blocksand/or operations can be used with any of the message flow diagrams,scenarios, and flow charts discussed herein, and these message flowdiagrams, scenarios, and flow charts can be combined with one another,in part or in whole.

A step or block that represents a processing of information cancorrespond to circuitry that can be configured to perform the specificlogical functions of a herein-described method or technique.Alternatively or additionally, a step or block that represents aprocessing of information can correspond to a module, a segment, or aportion of program code (including related data). The program code caninclude one or more instructions executable by a processor forimplementing specific logical operations or actions in the method ortechnique. The program code and/or related data can be stored on anytype of computer readable medium such as a storage device including RAM,a disk drive, a solid state drive, or another storage medium.

The computer readable medium can also include non-transitory computerreadable media such as computer readable media that store data for shortperiods of time like register memory and processor cache. The computerreadable media can further include non-transitory computer readablemedia that store program code and/or data for longer periods of time.Thus, the computer readable media may include secondary or persistentlong term storage, like ROM, optical or magnetic disks, solid statedrives, compact-disc read only memory (CD-ROM), for example. Thecomputer readable media can also be any other volatile or non-volatilestorage systems. A computer readable medium can be considered a computerreadable storage medium, for example, or a tangible storage device.

Moreover, a step or block that represents one or more informationtransmissions can correspond to information transmissions betweensoftware and/or hardware modules in the same physical device. However,other information transmissions can be between software modules and/orhardware modules in different physical devices.

The particular arrangements shown in the figures should not be viewed aslimiting. It should be understood that other embodiments can includemore or less of each element shown in a given figure. Further, some ofthe illustrated elements can be combined or omitted. Yet further, anexample embodiment can include elements that are not illustrated in thefigures.

While various aspects and embodiments have been disclosed herein, otheraspects and embodiments will be apparent to those skilled in the art.The various aspects and embodiments disclosed herein are for purpose ofillustration and are not intended to be limiting, with the true scopebeing indicated by the following claims.

What is claimed is:
 1. A performance analytics (PA) system disposed within a computational instance of a remote network management platform that is associated with a managed network and configured for processing and analysis of performance data of the managed network, the PA system comprising: a database containing a plurality of PA entity records, each PA entity record comprising data for configuring a graphical representation of a respective PA entity on a graphical user interface (GUI) within the managed network, wherein the respective PA entity is a component of the PA system configured for processing one or more key performance indicators (KPIs) of the managed network, and is implemented as at least one of a software component or a hardware system, and wherein each PA entity record further comprises information specifying a logical location of the respective PA entity in a dependency assessment tree, the dependency assessment tree comprising (i) respective nodes corresponding to the respective PA entities of the plurality of PA entity records and (ii) branches connecting nodes of PA entities between which there is a functional dependence; and a computing device operational to execute a dependency assessment software program, wherein the dependency assessment software program is configured to: transmit, to a client device, information for displaying in a GUI of the client device the graphical representation of one or more of the respective PA entities; receive, from the client device, a first request for dependency information for a first PA entity from among the one or more respective PA entities; and responsive to the first request, transmit, to the client device, a graphical representation of a first portion of the dependency assessment tree depicting the first PA entity and both one or more dependency nodes corresponding to PA entities having a functional dependency relationship with the first PA entity, and connecting branches.
 2. The PA system of claim 1, wherein the dependency assessment software program is further configured to: receive, from the client device, a second request for dependency information for a second PA entity from among the one or more dependency nodes depicted in the first portion of the dependency assessment tree; and responsive to the second request, transmit, to the client device, a graphical representation of a second portion of the dependency assessment tree depicting the second PA entity and both one or more dependency nodes corresponding to PA entities having a functional dependency relationship with the second PA entity, and connecting branches.
 3. The PA system of claim 1, wherein the respective nodes of the dependency assessment tree are arranged in a hierarchy of dependency levels, and wherein the one or more dependency nodes corresponding to the PA entities having a functional dependency relationship with the first PA entity comprise a collection of nodes, the collection of nodes consisting of at least one of: one or more nodes at one or more dependency levels below that of the first PA entity, or one or more nodes at one or more dependency levels above that of the first PA entity.
 4. The PA system of claim 3, wherein each of the one or more nodes at the one or more dependency levels below that of the first PA entity corresponds to a PA entity that the first PA entity functionally depends on, either directly or via one or more PA entities at one or more intervening dependency levels, wherein the first request for dependency information comprises a request for identification of the one or more nodes at the one or more dependency levels below that of the first PA entity, and wherein the first portion of the dependency assessment tree corresponds to a top-down view of the first PA entity and one or more of the PA entities that the first PA entity functionally depends on.
 5. The PA system of claim 3, wherein each of the one or more nodes at the one or more dependency levels above that of the first PA entity corresponds to a PA entity that functionally depends on the first PA, either directly or via one or more PA entities at one or more intervening dependency levels, wherein the first request for dependency information comprises a request for identification of the one or more nodes at the one or more dependency levels above that of the first PA entity, and wherein the first portion of the dependency assessment tree corresponds to a bottom-up view of the first PA entity and one or more PA entities that functionally depend on the first PA entity.
 6. The PA system of claim 1, wherein each PA entity is at least one of: a KPI, a dashboard, a dashboard tab, a scorecard, a widget, a breakdown, or a database.
 7. The PA system of claim 1, wherein the dependency assessment tree is derived from a KPI tree of KPIs of the managed network.
 8. The PA system of claim 1, wherein the dependency assessment software program is further configured to: receive, from the client device, an update message specifying a change to the first PA entity; based on the specified change to the first PA entity functionally, determine from among all respective PA entities that are functionally dependent on the first PA entity a conflict set of zero or more PA entities for which the specified change would result in erroneous operation; and transmit, to the client device, a graphical representation of the conflict set.
 9. A client device operable to configure a performance analytics (PA) system disposed within a computational instance of a remote network management platform that is associated with a managed network, the PA system being configured for processing and analysis of performance data of the managed network, the client device configured to: display, in a graphical user interface (GUI), a graphical representation of one or more PA entities, wherein a database of the remote network management platform contains a plurality of PA entity records, each PA entity record comprising data for configuring the graphical representation of a respective PA entity, wherein the respective PA entity is a component of the PA system configured for processing one or more key performance indicators (KPIs) of the managed network, and is implemented as at least one of a software component or a hardware system, and wherein each PA entity record further comprises information specifying a logical location of the respective PA entity in a dependency assessment tree, the dependency assessment tree comprising (i) respective nodes corresponding to the respective PA entities of the plurality of PA entity records and (ii) branches connecting nodes of PA entities between which there is a functional dependence; receive, via the GUI, input that selects a first PA entity from among the displayed one or more respective PA entities; responsive to transmitting, to a computing device disposed within the computational instance of the remote network management platform, a first request for dependency information for the selected first PA entity, receive a graphical representation of a first portion of the dependency assessment tree depicting the first PA entity and both one or more dependency nodes corresponding to PA entities having a functional dependency relationship with the first PA entity, and connecting branches; and display, in the GUI, the graphical representation of the first portion of the dependency assessment tree.
 10. The client device of claim 9, wherein the client device is further configured to: receive, via the GUI, input that selects a second PA entity from among the one or more dependency nodes depicted in the first portion of the dependency assessment tree; responsive to transmitting to the computing device a second request for dependency information for the selected second PA entity, receive a graphical representation of a second portion of the dependency assessment tree depicting the second PA entity and both one or more dependency nodes corresponding to PA entities having a functional dependency relationship with the second PA entity, and connecting branches; and display, in the GUI, the graphical representation of the second portion of the dependency assessment tree.
 11. The client device of claim 9, wherein the respective nodes of the dependency assessment tree are arranged in a hierarchy of dependency levels, and wherein the one or more dependency nodes corresponding to the PA entities having a functional dependency relationship with the first PA entity comprise a collection of nodes, the collection of nodes consisting of at least one of: one or more nodes at one or more dependency levels below that of the first PA entity, or one or more nodes at one or more dependency levels above that of the first PA entity.
 12. The client device of claim 11, wherein each of the one or more nodes at the one or more dependency levels below that of the first PA entity corresponds to a PA entity that the first PA entity functionally depends on, either directly or via one or more PA entities at one or more intervening dependency levels, wherein the first request for dependency information comprises a request for identification of the one or more nodes at the one or more dependency levels below that of the first PA entity, and wherein the first portion of the dependency assessment tree corresponds to a top-down view of the first PA entity and one or more of the PA entities that the first PA entity functionally depends on.
 13. The client device of claim 11, wherein each of the one or more nodes at the one or more dependency levels above that of the first PA entity corresponds to a PA entity that functionally depends on the first PA, either directly or via one or more PA entities at one or more intervening dependency levels, wherein the first request for dependency information comprises a request for identification of the one or more nodes at the one or more dependency levels above that of the first PA entity, and wherein the first portion of the dependency assessment tree corresponds to a bottom-up view of the first PA entity and one or more PA entities that functionally depend on the first PA entity.
 14. The client device of claim 9, wherein each PA entity is at least one of: a KPI, a dashboard, a dashboard tab, a scorecard, a widget, a breakdown, or a database.
 15. The client device of claim 9, wherein the dependency assessment tree is derived from a KPI tree of KPIs of the managed network.
 16. The client device of claim 9, wherein the client device is further configured to: transmit to the computing device an update message specifying a change to the first PA entity; receive from the computing device a graphical representation of a conflict set of PA entities identified from among all respective PA entities that are functionally dependent on the first PA entity, wherein the conflict set contains zero or more PA entities for which the specified change would result in erroneous operation; and display, in the GUI, the graphical representation of the conflict set if the conflict set is not empty.
 17. The client device of claim 9, wherein the dependency assessment tree further comprises a legend that contains a plurality of mappings between visual icons and performance analytics types of the respective PA entities, and wherein displaying the graphical representation of the first portion of the dependency assessment tree comprises displaying in a graphical representation of each of the one or more dependency nodes a visual icon corresponding one the visual icon of the legend.
 18. The client device of claim 9, wherein the client device is further configured to display a graphical drop-down menu of operations that can be applied to a given PA entity of a given one of the dependency nodes in response to a visual cursor hovering over a graphical representation of the given one of the dependency nodes.
 19. A method for configuring a performance analytics (PA) system disposed within a computational instance of a remote network management platform that is associated with a managed network, the PA system being configured for processing and analysis of performance data of the managed network, the method operable on a computing device disposed within the remote network management platform, the method comprising: transmitting, to a client device, information for displaying in a graphical user interface (GUI) of the client device a graphical representation of one or more respective PA entities, wherein a database of the remote network management platform contains a plurality of PA entity records, each PA entity record comprising data for configuring the graphical representation of a respective PA entity, wherein the respective PA entity is a component of the PA system configured for processing one or more key performance indicators (KPIs) of the managed network, and is implemented as at least one of a software component or a hardware system, and wherein each PA entity record further comprises information specifying a logical location of the respective PA entity in a dependency assessment tree, the dependency assessment tree comprising (i) respective nodes corresponding to the respective PA entities of the plurality of PA entity records and (ii) branches connecting nodes of PA entities between which there is a functional dependence; receiving, from the client device, a first request for dependency information for a first PA entity from among the one or more respective PA entities; and responsive to the first request, transmitting, to the client device, a graphical representation of a first portion of the dependency assessment tree depicting the first PA entity and both one or more dependency nodes corresponding to PA entities having a functional dependency relationship with the first PA entity, and connecting branches.
 20. The method of claim 19, further comprising: receiving, from the client device, a second request for dependency information for a second PA entity from among the one or more dependency nodes depicted in the first portion of the dependency assessment tree; and responsive to the second request, transmitting, to the client device, a graphical representation of a second portion of the dependency assessment tree depicting the second PA entity and both one or more dependency nodes corresponding to PA entities having a functional dependency relationship with the second PA entity, and connecting branches. 